Method for checking printability of a lithography target

ABSTRACT

A technique for determining, without having to perform optical proximity correction, when the result of optical proximity correction will fail to meet the design requirements for printability. A disclosed embodiment has application to a process for producing a photomask for use in the printing of a pattern on a wafer by exposure with optical radiation to optically image the photomask on the wafer. A method is set forth for checking the printability of a target layout proposed for defining the photomask, including the following steps: deriving a system of inequalities that expresses a set of design requirements with respect to the target layout; and checking the printability of the target layout by determining whether the system of inequalities is feasible.

RELATED APPLICATION

Priority is claimed from U.S. Provisional Patent Application No.60/709,881, filed Aug. 19, 2005, and said Provisional Patent Applicationis incorporated herein by reference.

FIELD OF THE INVENTION

This invention relates to the field of fabrication of integratedcircuits and, more particularly, to the checking for printability of alithography target used in the production of integrated circuits.

BACKGROUND OF THE INVENTION

Patterns in an integrated circuit are designed according to requirementsof circuit performance, layout and routing. The output of layout androuting is a set of target polygons that are input to photomask design.The goal of photomask design is to minimize the difference between thepattern that will be rendered on the wafer, and the target pattern, fora sufficiently large process window. Process window refers to a regionin the exposure dose-defocus plane on which one or more criticaldimension of a pattern is printed within an acceptable tolerance.Photomask design is an optimization process. Resolution enhancementtechniques (RET) and optical proximity corrections (OPC) are techniquesthat are used to optimize the photomask for a given target pattern.

An important consideration in chip design is that not every pattern canbe rendered by lithography. It is entirely possible to specify a targetpattern that is not printable, or printable with an unacceptably narrowprocess window, using a specific lithography process.

Layout and routing is constrained by a set of geometric design rules.For example, design rules may include minimum line width, minimum spacewidth, disallowed combinations of line and space widths. Conformance ofa target pattern to design rules is performed by a design rule check(DRC) software, which is based on geometry operations. A set of designrules is specific to a certain combination of wavelength, numericalaperture of the lithography projector, illumination condition, andphotoresist. Design rules are selected to ensure that if a patternconforms to the design rules, the pattern will be printable with asufficient process window.

However, design-rule checking of the prior art has deficiencies andlimitations, including the following: (1) there is no guarantee that afinite set of geometric rules can predict printability of countlesstwo-dimensional patterns; (2) if design rules ensure printability, theymay be overly conservative and may lead to increased chip size; (3)designers may choose to violate design rules to achieve a higher densityof devices, for example in an SRAM design.

If design rules are bypassed or design rules unwittingly allow a patternthat is not printable, RET and OPC can be thrown into an endless loop.If an RET/OPC approach fails to achieve a desired target pattern andprocess window, the natural reaction of the RET/OPC engineer is tochange the parameters of optimization, or to consider different RETschemes. This process can waste precious design time because prior artRET/OPC cannot definitively state that a certain target is unprintableirrespective of photomask technology at a given wavelength and numericalaperture (NA).

The prior art includes determination of printability after applyingoptical proximity corrections to the photomask layout (see: Choi et al.,Proceedings of SPIE, Vol. 5377, p. 713-720, SPIE Bellingham, Wash.,2004).

It is among the objects of the present invention to provide a techniquefor determining when the result of optical proximity corrections willfail to meet the design requirements, without having to perform theoptical proximity corrections. It is also among the objects of thepresent invention to improve on existing techniques for checking theprintability of a lithography target layout. [As used herein,“printability” of a target layout means that when the layout is employedin projecting an image on the wafer, the pattern that is printed (forexample, on a photoresist film coating of a wafer) by exposure withoptical radiation, has acceptable tolerances.]

SUMMARY OF THE INVENTION

The invention provides, inter alia, a technique for determining, withouthaving to perform optical proximity correction, when the result ofoptical proximity correction will fail to meet the design requirementsfor printability.

An embodiment of the invention has application to a process forproducing a photomask (e.g. a transmissive or reflective type ofphotomask) for use in the printing of a pattern on a wafer by exposurewith optical radiation to optically image the photomask on the wafer.[As used herein, “optical radiation” means light having wavelengthwithin or outside the visible, used to obtain exposure of a film, forexample a photoresist film.] In accordance with this embodiment, amethod is set forth for checking the printability of a target layoutproposed for defining said photomask, including the following steps:deriving a system of inequalities that expresses a set of designrequirements with respect to the target layout; and checking theprintability of said target layout by determining whether said system ofinequalities is feasible.

An embodiment of the invention further comprises dividing said targetlayout into parts, and the step of determining the printability of thetarget layout comprises determining the printability of said parts ofthe target layout.

In an embodiment of the invention, the photomask is for printing of apattern on a film on said wafer, and variations in the exposure dose oftarget points of the pattern are represented by dose latitude in saidsystem of inequalities. In a form of this embodiment, a determination ismade of a dose latitude for which at least part of the target layout isprintable.

In an embodiment of the invention, said system of inequalities includesthe wavelength of the optical radiation. Also this embodiment, theoptical radiation is produced by a projector having objective optics anda numerical aperture of its projection objective, and said system ofinequalities includes said numerical aperture, and also includes thedepth of field of the projector optics. Further in this embodiment, saidsystem of inequalities includes edge-placement tolerance of the patternassociated with the target layout. Also, a form of this embodimentincludes determination of an edge-placement tolerance for which at leastpart of said target pattern is printable.

In an embodiment of the invention, the step of checking the printabilityof said target layout is performed before performing at least one of thefollowing changes to said target layout: applying an optical proximitycorrection; adding a sub-resolution feature; or assigning a phase-shiftto a feature. In a form of this embodiment, the step of checking theprintability of said target layout is performed before an illuminationcondition of the photolithography projector is determined.

A further embodiment of the invention includes the following steps:providing a plurality of processors; and dividing said step ofdetermining the printability of said target layout among said pluralityof processors, whereby different processors determine the printabilityof different parts of said target layout.

An embodiment of the invention has application to the fabrication ofintegrated circuits that includes a process for producing a photomaskfor use in the printing of a pattern on a photoresist film which coatsat least part of a semiconductor wafer, by exposure with opticalradiation from a projector to optically image the photomask on thewafer. A method is set forth for checking the printability of a targetlayout proposed for defining said photomask, including the followingsteps: deriving a system of inequalities that expresses a set of designrequirements with respect to the target layout; dividing said targetlayout into parts; and checking the printability of said parts of saidtarget layout by determining whether said system of inequalities isfeasible. In a form of this embodiment, said checking is performedduring layout or routing of an integrated circuit. In a further form ofthis embodiment, the layout or routing is modified until printability isachieved.

The invention also has application to mask-less lithography andimmersion lithography. An embodiment hereof is broadly directed to aprocess for printing of a pattern on a wafer by optically projecting animage on the wafer. In accordance with this embodiment, a method is setforth for checking the printability of a target layout proposed fordefining said pattern, including the following steps: deriving a systemof inequalities that expresses a set of design requirements with respectto the target layout; and checking the printability of said targetlayout by determining whether said system of inequalities is feasible.

Further features and advantages of the invention will become morereadily apparent from the following detailed description when taken inconjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram showing a target polygon, target points,and some normal vectors.

FIG. 2 is a schematic diagram of a computation domain and a karocontaining a pattern.

FIG. 3 is a flow chart of a routine in accordance with an embodiment ofthe invention.

FIG. 4 is a block diagram of an apparatus in accordance with anembodiment of the invention.

DETAILED DESCRIPTION

The terms “karo”, “target points,” and “normal vectors” are used in thedescription, and will first be defined.

Techniques hereof check a small region of the target layer at a time.This region is called a karo. The union of karos cover the chip, or thepart of the layout to be checked. Karos may overlap. Karos arerectangular in a preferred embodiment, although in alternativeembodiments they can have any shape. The preferred size of a karo isbetween 0.5 and 2 micrometers for 193 nm exposure wavelength.

In a given karo, target points r₁,r₂, . . . , r_(M) are selected on theedges of target polygons. The target points are used to help encapsulatethe design requirements by a mathematical expression. In an embodimenthereof, target points on a polygon are approximately equally spaced by adistance of (k_(SAMPLE) λ/NA), where k_(SAMPLE) is a dimensionlessfactor that is less than 0.25 and preferably larger than 0.1; λ is theexposure wavelength, and NA is the numerical aperture of the lithographyprojector. In a preferred embodiment hereof, target points are notplaced on vertices of target polygons because sharp corners are notprintable.

In an embodiment hereof, a two-dimensional normal vector n_(j) isassigned to each target point r_(j). The normal vector is substantiallyperpendicular to the edge of the target polygon or the expected waferpattern. The normal vector points in the direction of increasing imageintensity. FIG. 1 shows a target polygon 110. In a preferred embodiment,target points 120 a, 120 b, . . . , 120 j, . . . are placed on a curve130 that fits the target polygon 110 except at the vertices. The unitvector that is perpendicular to the tangent of curve 130 at target point120 j is n_(j). In an alternative embodiment, the target points areplaced on the target polygon 110 avoiding its vertices, and the unitvector n_(j) is perpendicular to the edge of the target polygon attarget point 120 j.

In the following portion of the description, the design requirements fora preferred embodiment will be described in mathematical terms. Noprocess parameter can be held absolutely constant. There is anacceptable range of variation for any quantity that one wishes to keepconstant. Let (Δdose) be the accepted range of exposure dosevariability. Dose variations can be caused by changes in the thickness,refractive index, or extinction coefficient of the photoresist, or anyother film on the wafer. Dose variations can also be caused by temporalor spatial nonuniformity of the exposure intensity. Variations in thepost-exposure-bake temperature (PEB) can alter the dose threshold atwhich the resist dissolves upon development. Therefore, variations inthe PEB temperature are equivalent to a dose variation.

A goal of design for manufacturability (DFM) is to keep the edge of thepattern that will be printed on the wafer within an acceptable toleranceΔe of each target point when dose varies by Δdose. This requirement canbe expressed as a set of inequalities: $\begin{matrix}\begin{matrix}{{{{U\left( {r_{j} + {\Delta\quad e_{j}n_{j}}} \right)} \geq \frac{t}{1 - \frac{\Delta\quad{dose}}{dose}}};\quad{j = 1}},2,\ldots\quad,M} \\{{{{U\left( {r_{j} - {\Delta\quad e_{j}n_{j}}} \right)} \leq \frac{t}{1 + \frac{\Delta{dose}}{dose}}};\quad{j = 1}},2,\ldots\quad,M}\end{matrix} & (1)\end{matrix}$In the above system of inequalities, U(r) is the latent image intensityat a point r∈R² in the plane of the wafer; n_(j) is the unit normal ofthe pattern edge at the j^(th) target point r_(j); t is a threshold inthe units of image intensity such that the resist at r dissolves ifU(r)>t and does not dissolve if U(r)<t. The inequalities above ensurethat the resist edge will not deviate more than a distance of Δe_(j)from the target point r_(j) when the dose changes by a fractional amount±Δdose/dose. The first line in Equation (1) ensures that theedge-placement tolerance is met when the wafer is under exposed byΔdose. The second line in Equation (1) ensures that the edge-placementtolerance is met when the wafer is over exposed by Δdose.

To give a numerical example, the specification can be Δe=5 nm forΔdose/dose=5%. This specification ensures that critical dimension (linewidth) will not change by more than ±10 nm, and the contribution of thepresent layer to overlay will not exceed ±5 nm, when the dose changes by±5%.

In a preferred embodiment, the edge placement tolerance Δe_(j) can bedifferent for each target point r_(j). For example, in a gate layer of aCMOS ULSI chip, the edge-placement tolerance can be tighter (smaller) atthe edges that define the gate-lengths of transistors on a criticalcircuit, and Δe_(j) can be larger at the edges of interconnections inthe field poly-silicon. The tolerances can be tighter at the edges ofcontact landing pads whose placement is critical for overlay. Thetolerances can be derived from Boolean operations on patterns atmultiple layers and user-specified rules. In an alternative embodiment,all edge tolerances Δe_(j) are the same.

Inequality (1) encapsulates the design goals regarding the geometry ofthe desired pattern to be formed in photoresist, the edge placementtolerance, and the required dose latitude.

The latent image intensity is band-limited in the spatial-frequencydomain, or equivalently, wave-number domain. The latent image can beexpressed as a 2-dimensional Fourier integral:U(r)=∫exp(ik·r)Û(k)d ² k  (2)The Fourier transform variable k∈R² is a 2-dimensional wave-vector, andthe integral is taken over the entire 2-dimensional Euclidian space, andÛ(k) is the Fourier transform of U(r). The support of Û(k), that is theclosure of the set over which Û(k) takes non-zero values, is:Supp{Û}={k| ∥k∥≦k _(MAX)}  (3)k _(MAX)=4πNA/λ  (4)

Equation (4) expresses that the period of the highest spatial-frequencypattern that can be printed by an optical lithography projector isλ/(2NA).

If the pattern periodically repeats, then the latent image is aspatially-periodic pattern. In this case, the Fourier integral inEquation (2) reduces to a Fourier series with finitely many terms asshown in Equation (5a). Any portion of an arbitrary pattern can beapproximated by a periodic pattern for the purposes of imagecalculation, by stepping and repeating the portion of interest and somebuffer zone around it. $\begin{matrix}\begin{matrix}{{U(r)} = {\sum\limits_{m = {- M}}^{M}{\sum\limits_{n = {- N}}^{N}\left\{ {{\alpha_{mn}{\cos\left( {k_{mn} \cdot r} \right)}} + {\beta_{mn}{\sin\left( {k_{mn} \cdot r} \right)}}} \right\}}}} \\{k_{mn} = {2{\pi\left( {\frac{m}{\Lambda_{x}},\frac{n}{\Lambda_{y}}} \right)}}} \\{M = {{ceil}\left( {\Lambda_{x}{k_{MAX}/\left( {2\pi} \right)}} \right)}} \\{N = {{ceil}\left( {\Lambda_{y}{k_{MAX}/\left( {2\pi} \right)}} \right)}}\end{matrix} & \left( {5a} \right)\end{matrix}$

In Equation (5a), α_(mn) and β_(mn) are real-valued Fouriercoefficients; Λ_(x) is the period in the x-direction; Λ_(y) is theperiod in the y-direction; m and n are integer indices; ceil(x) standsfor the smallest integer that is greater than or equal to x; andk_(mn)·r denotes the inner-product of the vectors k_(mn) and r. Althoughit is not explicitly stated in Equation (5a), it is understood that onlylinearly independent combinations of sin(k_(mn)·r) and cos(k_(mn)·r) aretaken in the double summation. That is, if (m,n) is taken in thesummation, (−m,−n) is not taken, except when (m,n)=(0,0). The sin(k₀₀·r)term is not taken since that term would equal zero. Therefore, the firstline of (5a) can be more explicitly written as: $\begin{matrix}{{U(r)} = {\alpha_{00} + {\sum\limits_{\underset{{k_{0n}} \leq k_{MAX}}{n = 1}}^{N}\left\{ {{\alpha_{0n}{\cos\left( {k_{0n} \cdot r} \right)}} + {\beta_{0n}{\sin\left( {k_{0n} \cdot r} \right)}}} \right\}} + {\sum\limits_{m = 1}^{M}{\sum\limits_{\underset{{k_{mn}} \leq k_{MAX}}{n = {- N}}}^{N}\left\{ {{\alpha_{mn}{\cos\left( {k_{mn} \cdot r} \right)}} + {\beta_{mn}{\sin\left( {k_{mn} \cdot r} \right)}}} \right\}}}}} & \left( {5b} \right)\end{matrix}$

Only the terms that satisfy: $\begin{matrix}{{\frac{m^{2}}{\Lambda_{x}^{2}} + \frac{n^{2}}{\Lambda_{y}^{2}}} \leq \frac{k_{MAX}^{2}}{\left( {2\pi} \right)^{2}}} & (6)\end{matrix}$are taken in the summations in Equation (5). Equations (5) and (6)assume a rectangular array of unit cells of size Λ_(x) by Λ_(y). It ispossible to generalize (5) and (6) for arrays that are not rectangular.For example, a honeycomb is not a rectangular array, meaning the centersof its unit cells do not lie on lines that intersect each other at rightangles. For simplicity, non-rectangular arrays are not treated.

There are no more than (2M+1)(2N+1) terms in the series in Equation(5b). Most significantly, the latent image can be uniquely reconstructedfrom no more than (2M+1)(2N+1) real-valued coefficients (α_(mn) andβ_(mn)). In other words, the latent image is represented by no more than(2M+1)(2N+1) real numbers.

The image of a periodic pattern can also be represented by finitely manysamples of the image according to the Nyquist Sampling Theorem. Theimage can be sampled at points on a rectangular grid: $\begin{matrix}\begin{matrix}{s_{pq} = \begin{matrix}{{U\left( {{x_{0} + {p\quad{dx}}},{y_{0} + {q\quad{dy}}}} \right)};} & {{p = 1},2,\ldots\quad,{P;}} & {{q = 1},2,\ldots\quad,Q}\end{matrix}} \\{{dx} = {\frac{\Lambda_{x}}{P} < \frac{\pi}{k_{MAX}}}} \\{{dy} = {\frac{\Lambda_{y}}{Q} < \frac{\pi}{k_{MAX}}}}\end{matrix} & (7)\end{matrix}$The distances dx and dy are the sampling intervals along the x and yaxes, respectively. The integer indices p and q indicate that the imageintensity at the point (x₀+pdx, y₀+qdy) is s_(pq). The coordinate(x₀,y₀) is any convenient origin in the computation domain. According toNyquist theorem, the samples s_(pq); p=1,2, . . . , P; q=1,2, . . . , Quniquely determine the Fourier coefficients (α_(mn), β_(mn)) and viceversa. The Fourier coefficients are related to the samples by the linearequation: $\begin{matrix}{s = {\left\lbrack {A\quad B} \right\rbrack\begin{bmatrix}\alpha \\\beta\end{bmatrix}}} & (8)\end{matrix}$where s∈R^((PQ)) is a column vector containing the samples$\begin{matrix}{s = \begin{bmatrix}s_{11} \\s_{21} \\\vdots \\s_{PQ}\end{bmatrix}} & (9)\end{matrix}$The vector $\begin{bmatrix}\alpha \\\beta\end{bmatrix}\quad$of Fourier coefficients has two partitions: $\begin{matrix}{{\alpha = \begin{bmatrix}\alpha_{00} \\\alpha_{01} \\\vdots \\\alpha_{0N} \\\alpha_{1,{- N}} \\\vdots \\\alpha_{M,N}\end{bmatrix}};\quad{\beta = \begin{bmatrix}\quad \\\beta_{01} \\\vdots \\\beta_{0N} \\\beta_{1,{- N}} \\\vdots \\\beta_{M,N}\end{bmatrix}};} & (10)\end{matrix}$

There are no entries in the column vectors α and β corresponding to theindices m, n for which:${\frac{m^{2}}{\Lambda_{x}^{2}} + \frac{n^{2}}{\Lambda_{y}^{2}}} > {\frac{k_{MAX}^{2}}{\left( {2\pi} \right)^{2}}.}$The number of entries in $\quad\begin{bmatrix}\alpha \\\beta\end{bmatrix}$are less than or equal to, and typically less than, (2M+1)(2N+1). Thecoefficient matrix [A B] has two partitions. The entries of partition Aand B are: $\begin{matrix}\begin{matrix}{A_{p,{q;m},n} = {\cos\left( {{\left( {x_{0} + {pdx}} \right)\frac{2\pi\quad m}{\Lambda_{x}}} + {\left( {y_{0} + {qdy}} \right)\frac{2\pi\quad n}{\Lambda_{y}}}} \right)}} \\{B_{p,{q;m},n} = {\sin\left( {{\left( {x_{0} + {pdx}} \right)\frac{2\pi\quad m}{\Lambda_{x}}} + {\left( {y_{0} + {qdy}} \right)\frac{2\pi\quad n}{\Lambda_{y}}}} \right)}}\end{matrix} & (11)\end{matrix}$The indices p,q are mapped to a row number and the indices m,n aremapped to a column number. There are no columns in A and B correspondingto the indices m, n for which:${\frac{m^{2}}{\Lambda_{x}^{2}} + \frac{n^{2}}{\Lambda_{y}^{2}}} > {\frac{k_{MAX}^{2}}{\left( {2\pi} \right)^{2}}.}$The Fourier coefficients can be obtained from the samples as follows:$\begin{matrix}{{\begin{bmatrix}\alpha \\\beta\end{bmatrix} = {Cs}}{C = {\left( {\lbrack{AB}\rbrack^{T}\lbrack{AB}\rbrack} \right)^{- 1}\lbrack{AB}\rbrack}^{T}}} & (12)\end{matrix}$

The intensity at any point is calculated by the Fourier series:$\begin{matrix}{{{U\left( {x,y} \right)} = {{G\left( {x,y} \right)}s}}{G = {\begin{bmatrix}{D\left( {x,y} \right)} & {E\left( {x,y} \right)}\end{bmatrix}C}}{{D_{m,n}\left( {x,y} \right)} = {{{\cos\left( {\frac{2\pi\quad{mx}}{\Lambda_{x}} + \frac{2\pi\quad{ny}}{\Lambda_{y}}} \right)}{E_{m,n}\left( {x,y} \right)}} = {\sin\left( {\frac{2\pi\quad{mx}}{\Lambda_{x}} + \frac{2\pi\quad{ny}}{\Lambda_{y}}} \right)}}}} & (13)\end{matrix}$

The row vector D has as many entries as the column vector α. The indicesm, n are mapped to the column index of D. The row vector E has as manyentries as the column vector β. The indices m, n are mapped to thecolumn index of E. The row vectors D and E, and the row vector G dependon the position (x,y) at which the image intensity is evaluated. Thereare no entries in D and E corresponding to the indices m, n for which:${\frac{m^{2}}{\Lambda_{x}^{2}} + \frac{n^{2}}{\Lambda_{y}^{2}}} > {\frac{k_{MAX}^{2}}{\left( {2\pi} \right)^{2}}.}$

The image of any pattern in a karo can be approximated by the image of aperiodic pattern. This is illustrated by FIG. 2. A karo 210 is a subsetof a target pattern that is evaluated for printability. Each karo isevaluated separately. The union of karos cover the part of the patternedlayer that is subject to evaluation, which may be all of a patternedlayer. Karos may overlap, or they may be disjoint. Each karo 210 isembedded in a corresponding computation domain 220. At any point on theboundary of a karo, the distance 240 to the boundary of the computationdomain is greater than or equal to the length of optical influence whichis on the order of 3λ/NA. The image of the pattern calculated in thekaro is not influenced by the pattern outside the computation domain.Therefore, the pattern can be assumed to repeat periodically outside thecomputation domain. This approximation has negligible influence on theimage calculated at points inside the karo, if the buffer distance 240is large enough. This approximation allows the representation of theimage in the karo by a finite Fourier series as in Equation (5).

In the preferred embodiment, target points are placed in the karo and notarget points are placed outside the karo. The reason for this is thatthe image calculated outside the karo is potentially inaccurate due tothe periodicity assumption.

Some polygons in the target layout may intersect the boundary of thekaro 210 and/or the boundary of the computation domain 220. Effectively,in the image calculation, the polygons are clipped or cut at theboundary of the computation domain 220, and the pattern in thecomputation domain is stepped and repeated endlessly. No clipping ofpolygons occurs at the boundary of the karo 210.

In case the pattern is actually periodic, the distance 240 is zero; thekaro, the computation domain, and a unit cell of periodic pattern areone and the same.

Next, the feasibility of the design requirements will be treated. Thedesign requirements can be expressed as: $\begin{matrix}{{Ws} \leq h} & (14) \\{{W = \begin{bmatrix}{- {G\left( {r_{1} + {\Delta\quad{\mathbb{e}}\quad n_{1}}} \right)}} \\{- {G\left( {r_{2} + {\Delta\quad{\mathbb{e}}\quad n_{2}}} \right)}} \\\vdots \\{G\left( {r_{1} - {\Delta\quad{\mathbb{e}}\quad n_{1}}} \right)} \\{G\left( {r_{2} - {\Delta\quad{\mathbb{e}}\quad n_{2}}} \right)} \\\vdots \\{- I} \\I\end{bmatrix}};{h = \begin{bmatrix}{{- t}/\left\lbrack {1 - {\left( {\Delta\quad{dose}} \right)/{dose}}} \right\rbrack} \\{{- t}/\left\lbrack {1 - {\left( {\Delta\quad{dose}} \right)/{dose}}} \right\rbrack} \\\vdots \\{t/\left\lbrack {1 + {\left( {\Delta\quad{dose}} \right)/{dose}}} \right\rbrack} \\{t/\left\lbrack {1 + {\left( {\Delta\quad{dose}} \right)/{dose}}} \right\rbrack} \\\vdots \\0 \\{1U_{MAX}}\end{bmatrix}}} & (15)\end{matrix}$In inequality (14), Ws≦h means each entry of the column vector on theleft-hand-side is less than or equal to the corresponding entry of thecolumn vector on the right-hand-side. In Equation (15), the number ofcolumns of the identity matrix I is equal to the number of samples(length of vector s). The bold symbol 0 stands for a column vector suchthat its every entry is 0. The bold symbol 1 stands for a column vectorsuch that its every entry is 1. The positive number U_(MAX) is an upperbound for intensity at any point in the image. In a preferredembodiment, image intensity is normalized by the image intensity for aclear mask. Therefore, U_(MAX) is on the order of, but larger than, 1.The image intensity can exceed 1 due to constructive interference,especially when the illumination is highly coherent. For example, forannular illumination, U_(MAX)=1.2 is possible.

Inequality (14), Ws≦h , may or may not have a feasible set. Meaning,there may be no vector of samples s for which Ws≦h is true. In thatcase, it can be said the inequality Ws≦h and the design requirements areinfeasible. If Ws≦h is infeasible, there can be no image, and nophotomask design for which the design requirements will be met. Applyingsub-resolution assist features, using an alternating-aperturephase-shift mask (AA-PSM), using a custom optimized illumination, orusing the double-dipole method will not change the condition ofinfeasibility.

Checking the feasibility of an inequality is a well developed numericalmethod because it occurs in linear and quadratic programming.Fourier-Motzkin algorithm is one of the algorithms that are used todetermine the feasibility of a system of linear inequalities (see, forexample, Pablo A. Parrilo and Sanjay Lall, “Linear Inequalities andElimination,” Workshop presented at the 42nd IEEE Conference on Decisionand Control, Maui Hi., USA, Dec. 8th, 2003). In an alternativeembodiment, determining the feasibility of Ws≦h is transformed into alinear programming problem by the following transformation:$\begin{matrix}{{\min t}{{\overset{\sim}{W}\overset{\sim}{x}} = h}{\overset{\sim}{x} \geq 0}{\overset{\sim}{W} = \begin{bmatrix}W & {- W} & I & h\end{bmatrix}}{\overset{\sim}{x} = \begin{bmatrix}s_{+} \\s_{-} \\\xi \\t\end{bmatrix}}{s = {s_{+} - s_{-}}}} & (16)\end{matrix}$

In (16), the vectors s, s₊, s⁻ and ξ have the same dimensions. Allentries of the vectors s₊, s⁻ and ξ are non-negative; t is anon-negative scalar variable. The constraints of the minimization in(16) have a feasible starting point:$\overset{\sim}{x} = {\begin{bmatrix}s_{+} \\s_{-} \\\xi \\t\end{bmatrix} = {\begin{bmatrix}0 \\0 \\0 \\1\end{bmatrix}.}}$The vector {tilde over (x)} is not to be confused with thex-coordinates.Its entries are dimensionless, normalized image intensities. The linearcost function t in (16) attains a unique minimum t* at a solution {tildeover (x)}*. Ws≦h is feasible if and only if all entries of the vectorξ*+ht* are non-negative. The linear programming problem (16) can besolved using the Simplex Method (Linear Programming and its Extensions,George Danzig, Princeton University Press, 1993) or using Interior-pointmethods (Karmarkar, N. “A New Polynomial-Time Algorithm for LinearProgramming.” Combinatorica 4, 373-395, 1984; S. Mehrotra, “On theimplementation of a primal-dual interior point method,” SIAM Journal onOptimization, 2 (1992), pp. 575-601.)

FIG. 3 is a flow chart of a routine that can be used for controlling aprocessor or processors, such as the processors of FIG. 4, forimplementing an embodiment of the invention. The routine starts at 310,and block 320 represents selecting a karo and its buffer zone, whichtogether make up a computation domain. Target points are selected in thekaro, as represented by 330. The coefficient matrix and the right handside of the inequality Ws≦h are formed and stored, as represented byblock 340, according to Equation (15). Determination is then made(decision block 360) regarding the feasibility of the inequality Ws≦h.If Ws≦h is not feasible, the karo is marked as not printable (block 370)and the result is reported in a log file. If there is a feasible set,the karo is marked as “printable” (block 375). Determination is thenmade (decision block 380) as to whether any other region of the targetlayout remains to be checked. If there are no other regions to bechecked, the routine terminates at (block 390). Otherwise, block 320 isre-entered where a yet unchecked karo is selected, and the routinerepeats until all regions of interest of the target pattern are checked.

In an alternative embodiment, at step 370, when a karo is found to benot printable, (Δdose)/dose, i.e., the fractional dose latitude isreduced; and the feasibility of Ws≦h is checked again. The steps ofreducing and checking are repeated until one of the following happens: adose latitude at which Ws≦h is feasible is found; or a predeterminednumber of iterations or computation time is reached. The resultingreduced (Δdose)/dose is recorded. Thus, in this embodiment, not only isa weak area located, but its dose latitude is also evaluated for thegiven edge-placement tolerance.

In another embodiment, at step 370, when a karo is found to be notprintable, the edge placement tolerance, Δe, is increased and thefeasibility of Ws≦h is checked again. The steps of increasing andchecking are repeated until one of the following happens: anedge-placement tolerance at which Ws≦h is feasible is found; or apredetermined number of iterations or computation time is reached. Theresulting increased Δe is recorded. Thus, in this embodiment, not onlyis a weak area located, but its edge placement error is also evaluatedfor the given dose latitude.

Although k_(MAX) does not explicitly appear in Equation (15) or (13),the feasibility of Ws≦h is determined by k_(MAX). This is becausek_(MAX) effects A, B, D, E, and consequently W, through condition (6).In an alternative embodiment, feasibility is determined for a value ofk_(MAX) that is less than 4π NA/λ, such as: $\begin{matrix}{{k_{MAX} = \frac{4\pi\quad{NA}}{\lambda\left( {1 + {{safety}\quad{margin}}} \right)}}{{{safety}\quad{margin}} > 0}} & (17)\end{matrix}$In this alternative embodiment, when a pattern is determined to beprintable, it is printable with a safety margin.

In a preferred embodiment hereof, the printability is checked during thelayout and routing of the physical layout of an integrated circuit. Ifpart of any layer of the circuit is found to be not printable, thelayout and routing is changed until it becomes printable.

FIG. 4 is a block diagram of an apparatus 400 that can be used inpracticing an embodiment of the invention. The method described above iscoded as instructions, in a machine readable format, stored in a medium402, such as a CD, DVD, magnetic disk or tape. The instructions areloaded onto memory 445 of a processor 440 through an I/O device 410.Alternatively, the instructions can be loaded on the machine via anetwork. The processor 440 has storage system 420 that stores the targetlayout and the output data that indicates which regions are unprintable.The processor 440 has user interface 430 such as a keyboard, mouse, andscreen. Alternatively, the user interface can be on a remote computerlinked to system 400 via a network. The processor 440 has memory 445 tostore at least part of the target layout, instructions, and results ofintermediate calculations. In a preferred embodiment, processor 440 canbe one of many processors 440, 460 a, . . . , 460 z linked by ahigh-speed network 470. Processor 440 acts as a head node, which means,it divides up the computation into parts that can be performed inparallel, and assigns each part to one of the parallel processors 460.Upon completion of the said part of the computation, processor 460 sendsthe result through network 470 back to the head node 440, which collectsall such outputs and stores the end result in a file in storage 420.Head node 440 may assign a new karo to be checked to a processor 440when it becomes available. Performing the computation in parallelreduces the overall turn-around time of the computation. Each processor460 has associated memory 465 a, . . . , 465 z. Optionally, eachprocessor 460 may have its own storage device (not shown). In analternative embodiment, all of the computation is performed on onecomputer 440 and further processors 460 are not present.

ALTERNATIVE EMBODIMENT

In a preferred embodiment hereof, the left hand side of the inequalityis formed in terms of Fourier coefficients, α and β. The intensity atany point (x,y) can be expressed as: $\begin{matrix}{{{U\left( {x,y} \right)} = {\begin{bmatrix}{D\left( {x,y} \right)} & {E\left( {x,y} \right)}\end{bmatrix}\gamma}}{\gamma = \begin{bmatrix}\alpha \\\beta\end{bmatrix}}} & (18)\end{matrix}$

D and E are as defined in Equation (13). The intensity at Nyquistsampling points (Equation 9) can be written as ${s = {\begin{bmatrix}A & B\end{bmatrix}\gamma}},$

where A and B are defined in Equation (11). In addition to theedge-constraints defined in Equation (1), we can also enforceconstraints on the intensity values at Nyquist sampling points to ensurethat the image intensity is not marginally close to the threshold t inregions where it is intended to be dark or bright:

At the Nyquist points in regions of the image that are intended to bedark, image intensity must be greater than or equal to zero, and lessthan a pre-selected threshold t_(L) which in turn is less than or equalto the threshold t in Equation (1).

At the Nyquist points in features that are intended to be bright, imageintensity must be less than U_(MAX), and greater than a pre-selectedthreshold t_(U) which in turn is greater than or equal to t.

If a Nyquist sample point is closer to an edge of a feature than apredetermined distance δ, then the image intensity at that Nyquistsample point is constrained to be between 0 and U_(MAX). In analternative embodiment, no constraint is enforced at such a Nyquistsample point.

Let s_(D) be the array (vector) of intensities at the Nyquist points indark regions, s_(B) be the array of intensities at those points inbright regions, and s_(C) be the intensities at those points close tothe edges of polygons. We enforce the following constraints on theintensities at the Nyquist sample points:0≦s_(D)≦t_(L)<t<t_(U)≦s_(B)≦U_(MAX)  (19)0≦s_(C)≦U_(MAX)

In a preferred embodiment, the thresholds t_(L) and t_(U) are selectedas follows: $\begin{matrix}{{t_{L} = \frac{t}{1 + {\eta\frac{\Delta\quad{dose}}{dose}}}}{t_{U} = \frac{t}{1 - {\eta\frac{\Delta\quad{dose}}{dose}}}}{n > 1}} & (20)\end{matrix}$

In a preferred embodiment, the dimensionless factor η is an increasingfunction of the distance δ, which is the smallest possible distancebetween the Nyquist sampling points designated bright or dark, and anedge of a feature. Typically, η is between 1 and 2.

The constraints at the Nyquist sample points, and the edge-constraintsin Equation (1) can be put together to form a system of inequalities:$\begin{matrix}{{{{K\left( {r + {\Delta\quad{en}}} \right)}\gamma} \leq {{1U_{MAX}} - {K\left( {r + {\Delta\quad{en}}} \right)\gamma}} \leq {{- t}/\left\lbrack {1 - {\left( {\Delta\quad{dose}} \right)/{dose}}} \right\rbrack}}{{K\left( {r + {\Delta\quad{en}}} \right)\gamma} \leq {{{- t}/\left\lbrack {1 + {\left( {\Delta\quad{dose}} \right)/{dose}}} \right\rbrack} - {{K\left( {r - {\Delta\quad{en}}} \right)}\gamma}} \leq 0}{{H_{D}\gamma} \leq {{t/\left\lbrack {1 + {{\lambda\left( {\Delta\quad{dose}} \right)}/{dose}}} \right\rbrack} - {H_{D}\gamma}} \leq 0}{{H_{B}\gamma} \leq {{1U_{MAX}} - {H_{B}\gamma}} \leq {{- t}/\left\lbrack {1 - {{\lambda\left( {\Delta\quad{dose}} \right)}/{dose}}} \right\rbrack}}{{H_{C}\gamma} \leq {{1U_{MAX}} - {H_{C}\gamma}} \leq 0}} & (21)\end{matrix}$

In the above inequalities, H=[AB], and K(x,y)=[D(x,y) E(x,y)]. Thematrix K has as many rows as target points placed at the edges of thefeatures. The matrix H_(D) has as many rows as the number of Nyquistsampling points in features that are intended to be dark. The matrixH_(B) has as many rows as the number of Nyquist sampling points infeatures that are intended to be bright. The matrix H_(C) has as manyrows as the number of Nyquist sampling points that are closer than δ toan edge of a feature. Each line of (20) is a vector (array) ofinequalities. By concatenating the rows of (20) in to one matrixinequality, we obtain:Wγ≦h  (22)

W and h in (21) are different from the ones in the embodiment describedby Equation (15).

The embodiment described by Equations (14-15), and the embodimentdescribed by Equations (20-21) both involve determining the feasibilityof a system of inequalities. Feasibility of a system of inequalities canbe determined by any of several methods. Among these methods are:Fourier-Motzkin algorithm; linear programming methods such as theSimplex method or the interior-point methods as described above. Below,we describe two algorithms for determining the feasibility of a systemof inequalities. Both of these algorithms are more efficient than linearprogramming.

ALGORITHM (A) FOR DETERMINING THE FEASIBILITY OF Wγ≦h

We first introduce a vector of non-negative slack variables, ξ, totransform the inequality constraint into an equality constraint:Wγ+ξ=h;  (23)ξ≧0

The system of inequalities Wγ≦h is feasible if and only if there existsa slack vector ξ of non-negative entries which puts h−ξ in therange-space of matrix W. Thus determining the feasibility of the systemof inequalities is the same as determining if these two convex setsintersect:C ₁={ξ| ξ≧0} andC ₂={ξ| (ξ−h)∈RangeSpace(W)}  (24)

Let's call the orthogonal projectors of C₁ and C₂, P₁ and P₂,respectively. A point in the intersection of two convex sets can befound by successive, alternating projections on to the two convex sets.To form P₂, we do the QR-factorization of W=QR where columns of Q areorthonormal and R is an upper-triangular, square matrix of size rank(W).(Matrix Computations, G. H. Golub and C. F. Van Loan, Section 6.4, JohnHopkins University Press, 1983). The steps of algorithm A are asfollows:

-   -   1. Initialize ξ⁽⁰⁾=0, and define the vector θ=(I−QQ^(T))h    -   2. Iterate the following until convergence, or until a maximum        number of iterations is reached:        ξ^((k+1)) =P ₁(P ₂(ξ^((k))))=max(0, θ+QQ ^(T)ξ^((k))); k=0,1,2,        . . .        In a preferred embodiment, the criterion is ξ>−ε, where ε is a        small normalized-intensity tolerance such as 0.001.    -   3. Calculate the Fourier coefficients: γ=R⁻¹Q^(T)(h−ξ) and the        image intensity: Hγ.    -   4. Check if any entries of the inequality ξ>−ε are violated. If        so, record or graphically display the corresponding edge target        points or Nyquist sample points where the constraints are        violated.

In case of infeasibility, the convex sets C₁ and C₂ do not intersect,and the above equation converges to a realizable image intensity that isclosest to satisfying the constraints. In case of infeasibility, atleast some edge target points or Nyquist sample points are flagged. Thisindicates which features in the layout are infeasible in a locationspecific manner.

ALGORITHM (B) FOR DETERMINING THE FEASIBILITY OF Wγ≦h

In an alternative embodiment hereof, feasibility is determined bynonlinear minimization. The quantity that is minimized is:$\begin{matrix}{\min\limits_{\gamma}{{\min\left( {0,{h - {W\quad\gamma}}} \right)}}^{2}} & (25)\end{matrix}$

In (25), ∥x∥²=x^(T)x stands for the square of the l₂-norm of a vector.The min operator inside the norm selects, entry-by-entry, the lesser of0 or the entry of the vector h−Wγ. The minimal value of the norm is 0 ifand only if Wγ≦h is feasible. The minimization algorithm can be solvedby one of many optimization algorithms. In a preferred embodiment, (25)is minimized by the Gauss-Newton algorithm, which is useful forminimizing sum of squares. To this end, we define the vector-valuedresidual f(γ) and its Jacobian matrix J: $\begin{matrix}{{{f(\gamma)} = {\min\left( {0,{h - {W\quad\gamma}}} \right)}}{J_{ij} = {\frac{\partial f_{i}}{\partial\gamma_{j}} = \left\{ \begin{matrix}0 & {{{if}\quad f_{i}} = 0} \\{- W_{ij}} & {otherwise}\end{matrix} \right.}}} & (26)\end{matrix}$

The steps of algorithm B are as follows:

-   -   1. Initialize vector γ⁰. In a preferred embodiment,        $\gamma^{0} = {\underset{Ϛ}{\arg\quad\min}{{{h - {W\quad Ϛ}}}^{2}.}}$        In an alternative embodiment, γ⁰=0.    -   2. Iterate the following until convergence or until a maximum        number of iterations is reached:        ${{\gamma^{k + 1} = {\gamma^{k} + {\underset{Ϛ}{\arg\quad\min}{{{{J\left( \gamma^{k} \right)}Ϛ} + {f\left( \gamma^{k} \right)}}}}}},{k = 0},1,2,\ldots}\quad$    -   3. Calculate the image intensity Hγ.    -   4. Check if any entries of Wγ≦h are violated. If so, record or        graphically display the corresponding edge target points or        Nyquist sample points where the constraints are violated.

In the above iteration, argmin stands for: “the argument that minimizesthe following function.” Said minimization, which is a linear leastsquares problem, is with respect to the dummy vector ζ. The vector γ^(k)remains constant during the minimization in step 2. The solution of thelinear least squares problem$\min\limits_{Ϛ}{{{{J\left( \gamma^{k} \right)}Ϛ} + {f\left( \gamma^{k} \right)}}}$is well known (See: Matrix Computations, G. H. Golub and C. F. Van Loan,Chapter 6, John Hopkins University Press, 1983). In a preferredembodiment, the stopping criterion is: ∥f(γ^(k))∥<ε, for some small,normalized-image intensity ε such as 0.001. In case of infeasibility, atleast some edge target points or Nyquist sample points are flagged. Thisindicates which features in the layout are infeasible in alocation-specific manner.

The invention as been described with reference to particular preferredembodiments, but variations within the spirit and scope of the inventionwill occur to those skilled in the art. For example, the presentinvention is applicable to reflective as well as transmissivephotomasks. Reflective masks are required in extreme-ultra-violet (EUV)wavelengths. EUV lithography operates at about 13.5 nmexposure-wavelength. EUV masks are typically formed by alternatelydepositing thin films of two materials of dissimilar refractive indices,such as molybdenum and silicon. The periodic structure formed by thestack of alternating films has a stop-band which reflects the incomingradiation. The photomask pattern is etched into an absorptive film, suchas aluminum, deposited on top of the reflective stack of alternatingfilms (see: Stephen P. Vernon, et al., “Masks for extreme ultravioletlithography,” Proc. SPIE Vol. 3546, p. 184-193, December 1998, SPIEPress, Bellingham, Wash.).

The present invention is also applicable to mask-less lithography,wherein the photomask is replaced by a spatial light modulator. Thespatial light modulator has an array of pixels each of which canmodulate light that falls on it. The pixels are controlled according tothe photomask data. The spatial light modulator typically comprises anarray of micro-machined mirrors. The spatial light modulator isilluminated and its image is projected by an objective on to the wafer(see U.S. Pat. No. 6,700,095).

The present invention is also applicable to immersion lithography,wherein a transparent fluid such as water fills the gap between the lastlens of the projection objective and the photoresist film on thesemiconductor wafer. The refractive index of the fluid is higher thanthat of air.

The present invention is equally applicable to binary masks,attenuated-phase-shift masks, alternating aperture phase-shift masks,and multi-tone masks (masks having at least three portions of distincttransmission or reflection coefficients).

1. In a process for producing a photomask for use in the printing of apattern on a wafer by exposure with optical radiation to optically imagethe photomask on the wafer, a method for checking the printability of atarget layout proposed for defining said photomask, comprising the stepsof: deriving a system of inequalities that expresses a set of designrequirements with respect to said target layout; and checking theprintability of said target layout by determining whether said system ofinequalities is feasible.
 2. The method as defined by claim 1, whereinsaid target layout comprises data representative of the target layout,and wherein said step of determining printability of said target layoutis performed by at least one processor.
 3. The method as defined byclaim 2, further comprising the step of dividing said target layout intoparts, and wherein said step of determining the printability of saidtarget layout comprises determining the printability of said parts ofthe target layout.
 4. The method as defined by claim 3, furthercomprising providing an indication of non-printability for any parts ofsaid target layout determined to not be printable.
 5. The method asdefined by claim 2, wherein said photomask is for printing of a patternon a film on said wafer, and wherein variations in the exposure dose oftarget points of the pattern are represented by dose latitude in saidsystem of inequalities.
 6. The method as defined by claim 4, whereinsaid photomask is for printing of a pattern on a film on said wafer, andwherein variations in the exposure dose of target points of the patternare represented by dose latitude in said system of inequalities.
 7. Themethod as defined by claim 5, further comprising determining a doselatitude for which at least part of said target layout is printable. 8.The method as defined by claim 6, further comprising determining a doselatitude for which at least part of said target layout is printable. 9.The method as defined by claim 2, wherein said system of inequalitiesincludes the wavelength of said optical radiation.
 10. The method asdefined by claim 2, wherein said optical radiation is produced by aprojector having objective optics and a numerical aperture of itsprojection objective, and wherein said system of inequalities includessaid numerical aperture.
 11. The method as defined by claim 9, whereinsaid optical radiation is produced by a projector having objectiveoptics and a numerical aperture of its projection objective, and whereinsaid system of inequalities includes said numerical aperture.
 12. Themethod as defined by claim 2, wherein said system of inequalitiesincludes edge-placement tolerance of the pattern associated with thetarget layout.
 13. The method as defined by claim 12, wherein saidedge-placement tolerance is assigned different values at differentlocations.
 14. The method as defined by claim 13, wherein the value ofthe edge-placement tolerance is obtained by a Boolean operation onpatterns at more than one layer of a chip.
 15. The method as defined byclaim 11, wherein said system of inequalities includes edge-placementtolerance of the pattern associated with the target layout.
 16. Themethod as defined by claim 2, wherein said projector optics has a depthof field, and wherein said system of inequalities includes the depth offield of said projector optics.
 17. The method as defined by claim 5,wherein said projector optics has a depth of field, and wherein saidsystem of inequalities includes the depth of field of said projectoroptics.
 18. The method as defined by claim 2, wherein said determiningof whether said system of inequalities is feasible comprises employing aFourier-Motzkin algorithm.
 19. The method as defined by claim 2, whereinsaid determining of whether said system of inequalities is feasiblecomprises employing a Simplex algorithm.
 20. The method as defined byclaim 2, wherein said determining of whether said system of inequalitiesis feasible comprises employing an interior-point linear programmingalgorithm.
 21. The method as defined by claim 2, wherein saiddetermining of whether said system of inequalities is feasible comprisescalculating projections on convex sets.
 22. The method as defined byclaim 2, wherein said determining of whether said system of inequalitiesis feasible comprises minimizing a sum of squares.
 23. The method asdefined by claim 2, further comprising determining an edge-placementtolerance for which at least part of said target pattern is printable.24. The method as defined by claim 2, further comprising determiningprintability of said target layout with a predetermined safety margin.25. The method as defined by claim 3, further comprising the steps of:providing a plurality of processors; and dividing said step ofdetermining the printability of said target layout among said pluralityof processors, whereby different processors determine the printabilityof different parts of said target layout.
 26. The method as defined byclaim 2, wherein said step of checking the printability of said targetlayout is performed before performing at least one of the followingchanges to said target layout: applying an optical proximity correction;adding a sub-resolution feature; assigning a phase-shift to a feature.27. The method as defined by claim 2, wherein said step of checking theprintability of said target layout is performed before an illuminationcondition of a photolithography projector is determined.
 28. The methodas defined by claim 2, further comprising graphically displayinglocations at which design constraints are infeasible.
 29. In thefabrication of integrated circuits that includes a process for producinga photomask for use in the printing of a pattern on a photoresist filmwhich coats at least part of a semiconductor wafer, by exposure withoptical radiation from a projector to optically image the photomask onthe wafer, a method for checking the printability of a target layoutproposed for defining said photomask, comprising the steps of: derivinga system of inequalities that expresses a set of design requirementswith respect to said target layout; dividing said target layout intoparts; and checking the printability of said parts of said target layoutby determining whether said system of inequalities is feasible.
 30. Themethod as defined by claim 29, wherein said target layout comprises datarepresentative of the target layout, and wherein said step ofdetermining printability of said parts of said target layout isperformed by a plurality of processors.
 31. The method as defined byclaim 29, further comprising performing said checking during layout orrouting of an integrated circuit.
 32. The method as defined by claim 31,further comprising modifying said layout or routing until printabilityis achieved.
 33. In a process for printing of a pattern on a wafer byoptically projecting an image on the wafer, a method for checking theprintability of a target layout proposed for defining said pattern,comprising the steps of: deriving a system of inequalities thatexpresses a set of design requirements with respect to said targetlayout; and checking the printability of said target layout bydetermining whether said system of inequalities is feasible.
 34. Themethod as defined by claim 33, wherein said target layout comprises datarepresentative of the target layout, and wherein said step ofdetermining printability of said target layout is performed by at leastone processor.
 35. The method as defined by claim 34, further comprisingthe step of dividing said target layout into parts, and wherein saidstep of determining the printability of said target layout comprisesdetermining the printability of said parts of the target layout.